DBMS > BigObject vs. OpenQM vs. Sequoiadb vs. Weaviate

System Properties Comparison BigObject vs. OpenQM vs. Sequoiadb vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

QpenQM is a high-performance, self-tuning, multi-value DBMS

NewSQL database with distributed OLTP and SQL

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Multivalue DBMS

Document store
Relational DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

bigobject.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sequoiadb.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.bigobject.io

www.sequoiadb.com/en/index.php?m=Files&a=index

weaviate.io/developers/weaviate

Developer

BigObject, Inc.

Rocket Software, originally Martin Phillips

Sequoiadb Ltd.

Weaviate B.V.

Initial release

2015

1993

2013

2019

Current release

3.4-12

1.19, May 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPLv2, extended commercial license available

Open Source

Server: AGPL; Client: Apache V2

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

with some exceptions

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

string, int, float, geo point, date, cross reference, fuzzy references

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

GraphQL is used as query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

proprietary protocol using JSON

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C++
Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Lua

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights can be defined down to the item level

simple password-based access control

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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